DEDUPEDWhat do you want to do?
3 use cases
-
Extract structured entities from text with exact sources
Define a prompt and one good example, then extract entities tied to their exact text spans.
- REPO
google/langextract - Data and analytics
- Intermediate
View prompt
Using google/langextract, extract <entity types> from <document> with one example, and list each extraction with its source span. Verify three spans against the original text.
- REPO
-
Review extractions visually in context
Use the interactive visualization to check each extraction highlighted in the original text.
- REPO
google/langextract - Data and analytics
- Intermediate
View prompt
Generate a langextract visualization for <results> and report any extractions whose highlight does not match the attribute.
- REPO
-
Run extraction with OpenAI or a custom provider
Configure OpenAI models or add a custom model provider instead of the default.
View prompt
Run the same langextract job with two providers and compare extraction counts and grounding accuracy.
Quick start with LangExtract
- Check you have what it needs: Python; An API key for a cloud model, or a supported local or custom provider.
- Open google/langextract on GitHub and read the README and license.
- Install the LangExtract package
- Write a prompt describing what to extract
- Provide an ExampleData with Extraction entries
- Run extraction on your text and review the grounded results
These steps come from our top use case, Extract structured entities from text with exact sources, which also has a copy-paste agent prompt.
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About this repo
- Who it is forDevelopers and analysts pulling structured fields out of long documents such as reports, notes or literature.
- Why it is hot39k stars
- LanguagePython
- Sourcegithub.com/google/langextract · Back to Hot repos
Requirements
- Python
- An API key for a cloud model, or a supported local or custom provider
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Questions about LangExtract
What is LangExtract?
LangExtract is a Google Python library that uses LLMs to extract structured information from unstructured text with precise source grounding and an interactive visualization. It is an open-source project on GitHub: https://github.com/google/langextract.
Who is LangExtract for?
Developers and analysts pulling structured fields out of long documents such as reports, notes or literature.
What can I do with LangExtract?
3 use cases so far, for example: Extract structured entities from text with exact sources; Review extractions visually in context; Run extraction with OpenAI or a custom provider. Each has steps and a copy-paste agent prompt.
What do I need to run LangExtract?
Python; An API key for a cloud model, or a supported local or custom provider.
What are alternatives to LangExtract?
Other hot AI repos in Data and analytics: DSH Usage, Schemagate, Asobeast, Coreclaw API Directory, Open Index.
Is LangExtract safe to run?
Deduped does not own, audit or vouch for it. Read the README and license, run it on your own systems first and review every command before you run it.